on using probabilistic forwarding to improve hec-based data forwarding in opportunistic networks...
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On Using Probabilistic Forwarding On Using Probabilistic Forwarding to Improve HEC-based Data to Improve HEC-based Data Forwarding in Opportunistic Forwarding in Opportunistic
NetworksNetworks
Ling-Jyh ChenLing-Jyh Chen11, Cheng-Long Tseng, Cheng-Long Tseng22 and Cheng-Fu Chou and Cheng-Fu Chou22
11Academia SinicaAcademia Sinica22National Taiwan UniversityNational Taiwan University
MotivationMotivation
• There are numerous opportunistic networking applications.– wireless sensor network, underwater sensor
network, pocket switched network, people network, and transportation network
• Traditional data forwarding algorithms are not suitable for opportunistic networks.– Scheduled optimal routing method– Mobile relay approaches (Message ferry)
Related workRelated work
• Replication-based approaches– The messages are replicated. Several
identical copies are transmitted over the networks to mitigate the effects of a single path failure.
– For example:• Epidemic Routing, • Controlled Flooding, • mobility pattern-based scheme (Prophet)
Related workRelated work
• Coding-based approaches– Transforming a message into another
format prior to transmission.– For example:
• Erasure coding (EC), Aggressive Erasure Coding (A-EC), Hybrid Erasure Coding (H-EC)
• Network Coding
Our ContributionOur Contribution
• We propose a message scheduling algorithm, Probabilistic Forwarding, to improve H-EC scheme.
• Using a set of simulations, we show the proposed approach can provide better data delivery performance.
Overview of H-ECOverview of H-EC
• Erasure Coding:– Providing better fault-tolerance by
adding redundancy without the overhead of strict replication.• Reed-Solomon, • Low-Density Parity-Check (LDPC) based
coding (Gallager, Tornado, and IRA codes)
Erasure CodingErasure CodingA B C D
A-1
A-2
A-3
A-4
B-1
B-2
B-3 C-1
C-4
D-1
A B C D
A-1
A-2
A-3
A-4
B-1
B-2
B-3
B-4
C-1
C-2
C-3
C-4
D-1
D-2
D-3
D-4
Lossy Lossy ChannelChannel
(r,n)=(2,4)(r,n)=(2,4)
Overview of H-ECOverview of H-EC
• H-ECH-EC: Hybrid of EC and A-EC– First copy is sent using EC– Second copy is sent using A-EC during the
residual contact duration after sending the first EC block
The Purposed Method: HEC-The Purposed Method: HEC-PFPF
• Probabilistic forwarding– The HEC-PF scheme dost NOT enter the
aggressive forwarding phase unless a newly encountered node has a higher likelihood of successfully forwarding the message to the destination node that the current nodes.
• Delivery Probability
Delivery ProbabilityDelivery Probability
• Based on the observed contact history
• Take the contact frequency and contact volume into consideration.
• The proportion of time that the two nodes are in contact in the last T time units.
Delivery Probability
One-hop delivery probability
The ith Node
The source Node
The Destination
Node
the aggregated contact volume between the node pair Xi and Xj in the last T time units
K: number of nodes in the networkXi: the i-th node tXi;Xj:the aggregated contact volume between the node pair Xi and Xj in the last T time units
Delivery ProbabilityDelivery ProbabilityTwo-hop delivery probability
k-hop delivery probability
Three-hop delivery probability
Probabilistic ForwardingProbabilistic Forwarding
EvaluationEvaluation
• DTNSIM: A Java-based DTN simulator• Performance metric:
– Delay performance– Transmission overhead
• Evaluating Scenarios:
Evaluation I: two-hop Evaluation I: two-hop scenarioscenario
Power-Low Scenario ZebraNet Scenario UCSD Scenario
Evaluate the delay performance of the HEC-PF scheme for message delivery.Maximum message delivery distance (hops) H=2,
The transitive property of message delivery (hops) K=2
Evaluation II: Evaluation II: Variable Variable kk Scenarios Scenarios
ZebraNet Scenario UCSD Scenario
We evaluate the performance with various k values (k = 2,3,4,5)
Evaluation II: Evaluation II: Variable Variable kk Scenarios Scenarios
Evaluation III:Evaluation III:Variable Variable HH Scenarios Scenarios
ZibraNet Scenario UCSD Scenario
We evaluate the performance with various maximum forwarding distance settings (H = 2,3,4,5)
Evaluation II: Evaluation II: Variable Variable HH Scenarios Scenarios
ConclusionConclusion• We purposes a new scheme for data forwarding
by incorporating the basic H-EC scheme with a new feature, Probabilistic Forwarding.
• Using simulations as well as both synthetic and realistic network traces, we show that the proposed has better performance in terms of delivery latency and completion ratio.
• We show that the completion ratio improves as the maximum forwarding distance or the considered hop distance of the delivery probability increases.
Thank You!Thank You!